AI-powered application MouseAGE will use photos of lab animals to identify new therapeutics to treat aging and age-related diseases

NEW YORK, NY, August 29, 2017. Lifespan.io is launching a crowdfunding campaign to support MouseAGE, an application to assess visual biomarkers of aging in laboratory animals. This Artificial Intelligence-powered research tool, which is being developed by Youth Laboratories, will help scientists accurately determine the biological age of mice during experiments using advanced visual recognition and machine learning techniques. The project will help speed up research on rejuvenation therapeutics while collecting useful data in a more humane way.

The campaign has an initial goal of $30,000, is scheduled to run for 45 days, and has already received endorsements from several renowned aging researchers, such as Dr. Aubrey de Grey and Dr. Steve Horvath.

When we are looking at other people, we can easily determine their ages and even get a rough idea of their health by looking at their skin tone, pigmentation and elasticity, their hair color, and their other characteristics. However, the human eye cannot accurately determine subtle changes in the appearance of such tiny animals as mice, and this is where MouseAGE can help.

To rapidly collect data, commercial mouse breeders, research labs and application beta testers all over the world will take and upload many mouse photos to the database. By using machine learning combined with visual recognition, MouseAGE will learn to recognize mice from images, to define their body parts, and finally to detect the subtle visual biomarkers of aging. Detailed analysis of this data and detection of how it correlates with other biological phenomena will then allow researchers to assess potential anti-aging interventions during the early stages of their experiments and in a much less invasive way.

Anastasia Georgievskaya, co-founder and general manager at Youth Laboratories, says that the primary goal of the project is to increase the pace of research on aging while also reducing animal suffering in experiments:

“To eventually bring age-related diseases, such as Alzheimer’s and heart disease, under medical control, researchers need to identify therapies that slow down and reverse the main mechanisms of aging, such as DNA damage and protein waste accumulation. While animal data rarely translates to humans directly, studies in mice are providing valuable insights into many biological processes and make an important part of the drug development pipeline. Using animals in medical studies related to aging is currently unavoidable, but the application of AI through MouseAGE can help gather more data and process it in a more efficient way. This could reduce the number of animals in the experiments, and, in the future, it might allow researchers to replace some invasive tests with non-invasive tests. By developing MouseAGE, we are answering the call to make medical studies more humane.”

“There are many experiments conducted around the world that examine lifespan in mice. The artificially intelligent MouseAGE system will help determine which interventions make mice look younger. The plan is to develop an accurate predictor of mouse biological age based on images of mice and then apply transfer learning techniques to other datasets and data types,” says prof. Vadim Gladyshev, research lead of the project.

If successfully funded, the MouseAGE image collection tool will be available as a free mobile application by mid-October 2017. This will allow breeding houses and research institutions to begin collecting images and send them to the database. The project team hopes to collect enough data by February 2018 and will implement the algorithm for mouse age prediction by April 2018. This biomarker system will be made available as a free application shortly afterwards.

Media Contact

Anastasia Georgievskaya, the co-founder and general manager at Youth Laboratories, MouseAGE Project leader

Youth Laboratories is a company using artificial intelligence to analyze visual biomarkers of aging in order to help assess the efficiency of anti-aging therapeutics and anti-aging cosmetics. In 2015, Youth Laboratories, together with bioinformatics company Insilico Medicine, launched Beauty.AI 2.0, an app and beauty competition judged solely by artificial intelligence, and shortly after that – RYNKL, a wrinkle-analysis app.

As a devoted advocate of rejuvenation technologies since 2013, Elena is providing the community with a systemic vision how aging is affecting our society. Her research interests include global and local policies on aging, demographic changes, public perception of the application of rejuvenation technologies to prevent age-related diseases and extend life, and related public concerns. Elena is a co-author of the book “Aging prevention for all” (in Russian, 2015) and the organizer of multiple educational events helping the general public adopt the idea of eventually bringing aging under medical control.